Quant Researcher

Man Group•Boston, NY

7d•Hybrid

About The Position

Develop and improve quantitative investment strategies in equity markets within the Strategic Alpha Research team (SAR). Work across the full research lifecycle – from idea generation and data sourcing, through signal construction and testing, to portfolio construction and trade execution – supporting both new and existing strategies. The responsibilities include: Identifying new investment ideas or innovative data sources; Sourcing, gathering and refining complex data for modeling; Coding and performing statistical/ML analysis to build, test and refine predictive models; Interpreting, presenting, and implementing the results; Conducting research on various implementation aspects of investment strategies such as trading cost models, risk models, optimization, and portfolio construction. Contributing to the firm’s broader research agenda by collaborating with adjacent research teams, such as fixed income and macro, to share techniques, data and insights.

Requirements

Advanced degree in Computer Science, Statistics, Mathematics, Finance/Economics or related quantitative field
Passion for investment research
Strong intuition and the ability to think-out-of-the-box with a track record of original research and demonstrated problem solving ability
Excellent quantitative skills
Grounded in econometrics or statistics with extensive experience in utilizing those skills in empirical research
Strong programming skills (Python preferred)
Comfortable with analyzing large and complex data with statistical tools
Confident communicator; able to communicate complex ideas clearly
Good interpersonal skills to work together with the team
Self-organized; able to manage multiple projects and competing priorities
3+ years of experience in research

Nice To Haves

Prior experience in the investment field is a plus but not required
Hands-on experience across the full quant alpha lifecycle: data analysis, signal construction, monetization and live trading
Practical experience applying complex data modeling, ML, or LLMs/AI techniques to real investment problems

Responsibilities

Identifying new investment ideas or innovative data sources
Sourcing, gathering and refining complex data for modeling
Coding and performing statistical/ML analysis to build, test and refine predictive models
Interpreting, presenting, and implementing the results
Conducting research on various implementation aspects of investment strategies such as trading cost models, risk models, optimization, and portfolio construction
Contributing to the firm’s broader research agenda by collaborating with adjacent research teams, such as fixed income and macro, to share techniques, data and insights